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arxiv: 1509.06254 · v1 · pith:TG7M6KZLnew · submitted 2015-09-21 · 💻 cs.AI · cs.NI

Hybrid Optimization Algorithm for Large-Scale QoS-Aware Service Composition

classification 💻 cs.AI cs.NI
keywords compositionoptimalserviceshybridapproachcompositionsdatasetsextract
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In this paper we present a hybrid approach for automatic composition of Web services that generates semantic input-output based compositions with optimal end-to-end QoS, minimizing the number of services of the resulting composition. The proposed approach has four main steps: 1) generation of the composition graph for a request; 2) computation of the optimal composition that minimizes a single objective QoS function; 3) multi-step optimizations to reduce the search space by identifying equivalent and dominated services; and 4) hybrid local-global search to extract the optimal QoS with the minimum number of services. An extensive validation with the datasets of the Web Service Challenge 2009-2010 and randomly generated datasets shows that: 1) the combination of local and global optimization is a general and powerful technique to extract optimal compositions in diverse scenarios; and 2) the hybrid strategy performs better than the state-of-the-art, obtaining solutions with less services and optimal QoS.

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